Heart failure management

ABSTRACT

Various system embodiments comprise a stimulator adapted to deliver a stimulation signal for a heart failure therapy, a number of sensors adapted to provide at least a first measurement of a heart failure status and a second measurement of the heart failure status, and a controller. The controller is connected to the stimulator and to the number of sensors. The controller is adapted to use the first and second measurements to create a heart failure status index, and control the stimulator to modulate the signal using the index. Other aspects and embodiments are provided herein.

CLAIM OF PRIORITY

This application is a continuation of and claims the benefit of priorityunder 35 U.S.C. §120 to U.S. patent application Ser. No. 13/731,691,filed on Dec. 31, 2012, now issued as U.S. Pat. No. 8,620,427, which isa continuation of and claims the benefit of priority under 35 U.S.C.§120 to U.S. patent application Ser. No. 13/214,564, filed on Aug. 22,2011, now issued as U.S. Pat. No. 8,346,360, which is a continuation ofand claims the benefit of priority under 35 U.S.C. §120 to U.S. patentapplication Ser. No. 11/382,128, filed on May 8, 2006, now issued asU.S. Pat. No. 8,005,543, each of which is hereby incorporated byreference herein in its entirety.

FIELD OF THE INVENTION

This application relates generally to medical devices and, moreparticularly, to systems, devices and methods for managing heart failureusing neural stimulation.

BACKGROUND

Heart failure refers to a clinical syndrome in which cardiac functioncauses a below normal cardiac output that can fall below a leveladequate to meet the metabolic demand of peripheral tissues. Heartfailure may present itself as congestive heart failure (CHF) due to theaccompanying venous and pulmonary congestion. Heart failure can be dueto a variety of etiologies such as ischemic heart disease. Cardiacdecompensation is typically marked by dyspnea (difficulty breathing),venous engorgement and edema, and each decompensation event can causefurther long term deterioration of the heart function.

Heart failure patients have reduced autonomic balance, which isassociated with left ventricular dysfunction and increased mortality.Modulation of the sympathetic and parasympathetic nervous systems haspotential clinical benefit in preventing remodeling and death in heartfailure and post-MI (myocardial infarction) patients.

Clinicians set measured parameter thresholds in some known implantablemedical devices, such as pacemakers, defibrillators, cardiacresynchronization devices, and the like. The threshold for eachparameter may vary from patient to patient. Appropriate device therapyis triggered when a threshold is crossed. Treatment can be initiated bynon-events that include measurements above at least some thresholds.These non-events are also referred to as false positives. Therapydelivered for false positives depletes battery power and may increasethe risk of overstimulating the patient.

Improved methods and systems are needed to accurately determine heartfailure status, and to provide heart failure therapy using theaccurately-determined heart failure status.

SUMMARY

Various aspects of the present subject matter relate to a system.Various system embodiments comprise a stimulator adapted to deliver astimulation signal for a heart failure therapy, a number of sensorsadapted to provide at least a first measurement of a heart failurestatus and a second measurement of the heart failure status, and acontroller. The controller is connected to the stimulator and to thenumber of sensors. The controller is adapted to use the first and secondmeasurements to create a heart failure status index, and control thestimulator to modulate the signal using the index.

Various aspects of the present subject matter relate to a method.According to various embodiments of the method, a first measurement of aheart failure status and a second measurement of the heart failurestatus are obtained. A heart failure index is created using the firstmeasurement and the second measurement. A heart failure therapy isadjusted using the heart failure index as an indicator of the heartfailure status.

This Summary is an overview of some of the teachings of the presentapplication and not intended to be an exclusive or exhaustive treatmentof the present subject matter. Further details about the present subjectmatter are found in the detailed description and appended claims. Otheraspects will be apparent to persons skilled in the art upon reading andunderstanding the following detailed description and viewing thedrawings that form a part thereof, each of which are not to be taken ina limiting sense. The scope of the present invention is defined by theappended claims and their equivalents.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A shows an example of a probability density function p_(i)(x|H₀)based upon measurements taken over a period time for a physiologicalparameter of a patient; FIG. 1B shows one example of the non-eventprobability density function p(x_(i)|H₀); and FIG. 1C shows anotherexample, in which a function p_(j)(x|H₀) is represented by anegative-tailed distribution of measurements for a physiologicalparameter, such as may be used to determine when to deliver HF therapy,according to various embodiments.

FIG. 2 illustrates system having a plurality of data sources ofparameters related to heart failure coupled to an intelligent system,such as may be used to determine when to deliver HF therapy, accordingto various embodiments.

FIGS. 3A-3C illustrate the effectiveness of neural stimulation as a HFtherapy.

FIG. 4A illustrates transvascularly fed leads, and FIG. 4B illustratesepicardial leads for a heart, which may be used in some therapies.

FIGS. 5A and 5B illustrate the right side and left side of the heart,respectively, and further illustrate cardiac fat pads which provideneural targets for some neural stimulation therapies.

FIG. 6 illustrates a device embodiment to generate a sensed HF statusindex using two or more HF-related parameters and controlling neuralstimulation to an HF-therapy neural target.

FIG. 7 illustrates a device embodiment to generate a chronic orlong-term sensed HF status index and an acute or short-term sensed HFstatus index using two or more HF-related parameters, and controllingneural stimulation to an HF-therapy neural target using the indices.

FIG. 8 illustrates a method for controlling an HF therapy, according tovarious embodiments of the present subject matter.

FIG. 9 illustrates a method for controlling an HF therapy, according tovarious embodiments of the present subject matter.

FIG. 10 illustrates an implantable medical device (IMD), according tovarious embodiments of the present subject matter.

FIG. 11 illustrates an implantable medical device (IMD) having a neuralstimulation (NS) component and cardiac rhythm management (CRM)component, according to various embodiments of the present subjectmatter.

FIG. 12 shows a system diagram of an embodiment of amicroprocessor-based implantable device, according to variousembodiments.

FIG. 13 illustrates a system including an implantable medical device(IMD) and an external system or device, according to various embodimentsof the present subject matter.

FIG. 14 illustrates a system including an external device, animplantable neural stimulator (NS) device and an implantable cardiacrhythm management (CRM) device, according to various embodiments of thepresent subject matter.

FIG. 15 illustrates an IMD placed subcutaneously or submuscularly in apatient's chest with lead(s) positioned to provide a CRM therapy to aheart, and with lead(s) positioned to stimulate and/or inhibit neuraltraffic in a vagus nerve, by way of example and not by way oflimitation, according to various embodiments.

FIG. 16 illustrates an IMD with lead(s) positioned to provide a CRMtherapy to a heart, and with satellite transducers positioned tostimulate/inhibit a neural target, according to various embodiments.

FIG. 17 is a block diagram illustrating an embodiment of an externalsystem.

DETAILED DESCRIPTION

The following detailed description of the present subject matter refersto the accompanying drawings which show, by way of illustration,specific aspects and embodiments in which the present subject matter maybe practiced. These embodiments are described in sufficient detail toenable those skilled in the art to practice the present subject matter.Other embodiments may be utilized and structural, logical, andelectrical changes may be made without departing from the scope of thepresent subject matter. References to “an”, “one”, or “various”embodiments in this disclosure are not necessarily to the sameembodiment, and such references contemplate more than one embodiment.The following detailed description is, therefore, not to be taken in alimiting sense, and the scope is defined only by the appended claims,along with the full scope of legal equivalents to which such claims areentitled.

The present subject matter provides an index for heart failure (HF)status using at least two measured HF parameters. Embodiments provide aclosed-loop neural stimulation system for heart failure (HF) therapythat modulates the therapy based on a heart failure status. Embodimentsof the system include an implantable neural stimulator. Aneurostimulation therapy is applied to prevent or slow reverseremodeling in HF patients. The HF status is determined by a combinationof physiological variables derived from a suite of physiologicalsensors. For example, the HF status can be determined as a compositeindex using two or more measured parameters related to HF status.Examples of measured parameters related to HF status include heart ratevariability (HRV), heart rate turbulence (HRT), heart sounds, activity,transthoracic impedance, minute ventilation, pulmonary artery pressure,and electrogram features.

Neural stimulation parameter modulation can occur in response to changesin any or all of the parameters used to create the HF status index. Someof the measured parameters that make up the index can be updatedcontinuously within the constraints of the device(s) used to perform themeasurements, while other measured parameters are updated intermittentlyor updated periodically (e.g. hourly, daily, etc.). Various embodimentstrend the parameters to monitor changes. Indices of chronic worseningheart failure (such as lower SDANN for an HRV analysis, higher minimumheart rate, weaker RSA coupling and physiologic response to activity aswill be discussed below) triggers a shift towards neural stimulationtherapy to elicit a parasympathetic response (stimulatingparasympathetic nerve traffic and/or inhibiting sympathetic nervetraffic), and indices of improving heart failure (reversed trend of theindices above) triggers a shift away from eliciting a parasympatheticresponse (e.g. reduce intensity of stimulation) or trigger a shift toelicit a sympathetic response (stimulating sympathetic nerve trafficand/or inhibiting parasympathetic nerve traffic). HRV, SDANN and RSA arediscussed below. Neural stimulation parameters include amplitude,frequency, duty cycle, pulse width, and stimulation site, and any or allof these parameters can be modulated to shift autonomic balance towardsgreater or lesser parasympathetic response or between a parasympatheticresponse and a sympathetic response.

Control systems according to embodiments of the present subject matterefficiently manage battery power and reduce the risk of patientover-stimulation by reducing false positives. Embodiments of the devicehave a dual feedback response to account for long-term and short-termchanges. Variables indicative of chronic changes in heart failure statusare used to titrate the application of neural stimulation therapy (e.g.increased parasympathetic stimulation in response to worsening heartfailure status). The dual feedback device embodiments also respond tovariables indicative of short-term changes in HF status (e.g. anapproaching decompensation event) and apply emergency neural stimulationtherapy to prevent or delay the decompensation event. For example,appropriate neural stimulation can be provided to elicit an appropriatesympathetic response for a short term to maintain cardiac output untilthe patient can reach a clinical setting.

Various device embodiments provide cardiac rhythm management therapy,including pacing, defibrillation, and/or cardiac resynchronizationtherapy, and use the HF status to control these therapies. Someembodiment provide a CRM therapy in addition to a neural stimulation HFtherapy. The feedback sensors can be integrated into the implantabledevice, or external to the body, or both. The device can wirelesslycommunicate with an external monitor, allowing the system to monitor,record, and trend HF status and therapy application, and to providealerts based on changes in HF status.

The discussion that follows is organized into a brief discussion ofphysiology, examples of HF status parameters, a discussion of the HFstatus index based on at least two HF status parameters, a discussion oftherapies including neural stimulation and myocardial stimulation,device embodiments and system embodiments.

Physiology

Provided below is a brief discussion of the nervous system, heartfailure, hypertension and cardiac remodeling. This discussion isbelieved to assist a reader in understanding the disclosed subjectmatter.

Nervous System

The autonomic nervous system (ANS) regulates “involuntary” organs, whilethe contraction of voluntary (skeletal) muscles is controlled by somaticmotor nerves. Examples of involuntary organs include respiratory anddigestive organs, and also include blood vessels and the heart. Often,the ANS functions in an involuntary, reflexive manner to regulateglands, to regulate muscles in the skin, eye, stomach, intestines andbladder, and to regulate cardiac muscle and the muscle around bloodvessels, for example.

The ANS includes, but is not limited to, the sympathetic nervous systemand the parasympathetic nervous system. The sympathetic nervous systemis affiliated with stress and the “fight or flight response” toemergencies. Among other effects, the “fight or flight response”increases blood pressure and heart rate to increase skeletal muscleblood flow, and decreases digestion to provide the energy for “fightingor fleeing.” The parasympathetic nervous system is affiliated withrelaxation and the “rest and digest response” which, among othereffects, decreases blood pressure and heart rate, and increasesdigestion to conserve energy. The ANS maintains normal internal functionand works with the somatic nervous system. Afferent nerves conveyimpulses toward a nerve center, and efferent nerves convey impulses awayfrom a nerve center.

The heart rate and force is increased when the sympathetic nervoussystem is stimulated, and is decreased when the sympathetic nervoussystem is inhibited (the parasympathetic nervous system is stimulated).Cardiac rate, contractility, and excitability are known to be modulatedby centrally mediated reflex pathways. Baroreceptors and chemoreceptorsin the heart, great vessels, and lungs, transmit cardiac activitythrough vagal and sympathetic afferent fibers to the central nervoussystem. Activation of sympathetic afferents triggers reflex sympatheticactivation, parasympathetic inhibition, vasoconstriction, andtachycardia. In contrast, parasympathetic activation results inbradycardia, vasodilation, and inhibition of vasopressin release. Amongmany other factors, decreased parasympathetic or vagal tone or increasedsympathetic tone is associated with various arrhythmias genesis,including ventricular tachycardia and atrial fibrillation.

Baroreflex is a reflex triggered by stimulation of a baroreceptor. Abaroreceptor includes any sensor of pressure changes, such as sensorynerve endings in the wall of the auricles of the heart, vena cava,aortic arch and carotid sinus, that is sensitive to stretching of thewall resulting from increased pressure from within, and that functionsas the receptor of the central reflex mechanism that tends to reducethat pressure. Clusters of nerve cells can be referred to as autonomicganglia. These nerve cells can also be electrically stimulated to inducea baroreflex, which inhibits the sympathetic nerve activity andstimulates parasympathetic nerve activity. Autonomic ganglia thus formspart of a baroreflex pathway. Afferent nerve trunks, such as the vagus,aortic and carotid nerves, leading from the sensory nerve endings alsoform part of a baroreflex pathway. Stimulating a baroreflex pathwayand/or baroreceptors inhibits sympathetic nerve activity (stimulates theparasympathetic nervous system) and reduces systemic arterial pressureby decreasing peripheral vascular resistance and cardiac contractility.Baroreceptors are naturally stimulated by internal pressure and thestretching of vessel wall (e.g. arterial wall).

Stimulating the sympathetic and parasympathetic nervous systems can haveeffects other than heart rate and blood pressure. For example,stimulating the sympathetic nervous system dilates the pupil, reducessaliva and mucus production, relaxes the bronchial muscle, reduces thesuccessive waves of involuntary contraction (peristalsis) of the stomachand the motility of the stomach, increases the conversion of glycogen toglucose by the liver, decreases urine secretion by the kidneys, andrelaxes the wall and closes the sphincter of the bladder. Stimulatingthe parasympathetic nervous system (inhibiting the sympathetic nervoussystem) constricts the pupil, increases saliva and mucus production,contracts the bronchial muscle, increases secretions and motility in thestomach and large intestine, and increases digestion in the smallintention, increases urine secretion, and contracts the wall and relaxesthe sphincter of the bladder. The functions associated with thesympathetic and parasympathetic nervous systems are many and can becomplexly integrated with each other.

Neural stimulation can be used to stimulate nerve traffic or inhibitnerve traffic. An example of neural stimulation to stimulate nervetraffic is a lower frequency signal (e.g. within a range on the order of20 Hz to 50 Hz). An example of neural stimulation to inhibit nervetraffic is a higher frequency signal (e.g. within a range on the orderof 120 Hz to 150 Hz). Other methods for stimulating and inhibiting nervetraffic has been proposed. According to various embodiments of thepresent subject matter, sympathetic neural targets include, but are notlimited to, a peroneal nerve, a sympathetic column in a spinal cord, andcardiac post-ganglionic sympathetic neurons. According to variousembodiments of the present subject matter, parasympathetic neuraltargets include, but are not limited to, a vagus nerve, a baroreceptor,and a cardiac fat pad.

Heart Failure

Heart failure refers to a clinical syndrome in which cardiac functioncauses a below normal cardiac output that can fall below a leveladequate to meet the metabolic demand of peripheral tissues. Heartfailure may present itself as congestive heart failure (CHF) due to theaccompanying venous and pulmonary congestion. Heart failure can be dueto a variety of etiologies such as ischemic heart disease. Heart failurepatients have reduced autonomic balance, which is associated with LVdysfunction and increased mortality. Modulation of the sympathetic andparasympathetic nervous systems has potential clinical benefit inpreventing remodeling and death in heart failure and post-MI patients.Direct electrical stimulation can activate the baroreflex, inducing areduction of sympathetic nerve activity and reducing blood pressure bydecreasing vascular resistance. Sympathetic inhibition andparasympathetic activation have been associated with reduced arrhythmiavulnerability following a myocardial infarction, presumably byincreasing collateral perfusion of the acutely ischemic myocardium anddecreasing myocardial damage.

Hypertension

Hypertension is a cause of heart disease and other related cardiacco-morbidities. Hypertension occurs when blood vessels constrict. As aresult, the heart works harder to maintain flow at a higher bloodpressure, which can contribute to heart failure. Hypertension generallyrelates to high blood pressure, such as a transitory or sustainedelevation of systemic arterial blood pressure to a level that is likelyto induce cardiovascular damage or other adverse consequences.Hypertension has been arbitrarily defined as a systolic blood pressureabove 140 mm Hg or a diastolic blood pressure above 90 mm Hg.Consequences of uncontrolled hypertension include, but are not limitedto, retinal vascular disease and stroke, left ventricular hypertrophyand failure, myocardial infarction, dissecting aneurysm, andrenovascular disease.

A large segment of the general population, as well as a large segment ofpatients implanted with pacemakers or defibrillators, suffer fromhypertension. The long term mortality as well as the quality of life canbe improved for this population if blood pressure and hypertension canbe reduced. Many patients who suffer from hypertension do not respond totreatment, such as treatments related to lifestyle changes andhypertension drugs.

Cardiac Remodeling

Following myocardial infarction (MI) or other cause of decreased cardiacoutput, a complex remodeling process of the ventricles occurs thatinvolves structural, biochemical, neurohormonal, and electrophysiologicfactors. Ventricular remodeling is triggered by a physiologicalcompensatory mechanism that acts to increase cardiac output due toso-called backward failure which increases the diastolic fillingpressure of the ventricles and thereby increases the so-called preload(i.e., the degree to which the ventricles are stretched by the volume ofblood in the ventricles at the end of diastole). An increase in preloadcauses an increase in stroke volume during systole, a phenomena known asthe Frank-Starling principle. When the ventricles are stretched due tothe increased preload over a period of time, however, the ventriclesbecome dilated. The enlargement of the ventricular volume causesincreased ventricular wall stress at a given systolic pressure. Alongwith the increased pressure-volume work done by the ventricle, this actsas a stimulus for hypertrophy of the ventricular myocardium. Thedisadvantage of dilatation is the extra workload imposed on normal,residual myocardium and the increase in wall tension (Laplace's Law)which represent the stimulus for hypertrophy. If hypertrophy is notadequate to match increased tension, a vicious cycle ensues which causesfurther and progressive dilatation.

As the heart begins to dilate, afferent baroreceptor and cardiopulmonaryreceptor signals are sent to the vasomotor central nervous systemcontrol center, which responds with hormonal secretion and sympatheticdischarge. It is the combination of hemodynamic, sympathetic nervoussystem and hormonal alterations (such as presence or absence ofangiotensin converting enzyme (ACE) activity) that ultimately accountfor the deleterious alterations in cell structure involved inventricular remodeling. The sustained stresses causing hypertrophyinduce apoptosis (i.e., programmed cell death) of cardiac muscle cellsand eventual wall thinning which causes further deterioration in cardiacfunction. Thus, although ventricular dilation and hypertrophy may atfirst be compensatory and increase cardiac output, the processesultimately result in both systolic and diastolic dysfunction(decompensation). It has been shown that the extent of ventricularremodeling is positively correlated with increased mortality in post-MIand heart failure patients.

HF Status Parameters

Examples of parameters that can be used to determine a HF status includeheart rate variability (HRV), heart rate turbulence (HRT), heart sounds,electrogram features, activity, respiration, and pulmonary arterypressure. These parameters are briefly discussed below.

Respiration parameters, for example, can be derived from a minuteventilation signal and a fluid index can be derived from transthoracicimpedance. For example decreasing thoracic impedance reflects increasedfluid buildup in lungs, and indicates a progression of heart failure.Respiration can significantly vary a minute ventilation. Thetransthoracic impedance can be totaled or averaged to provide aindication of fluid buildup.

HRV

Heart Rate Variability (HRV) is one technique that has been proposed toassess autonomic balance. HRV relates to the regulation of thesinoatrial node, the natural pacemaker of the heart by the sympatheticand parasympathetic branches of the autonomic nervous system. An HRVassessment is based on the assumption that the beat-to-beat fluctuationsin the rhythm of the heart provide us with an indirect measure of hearthealth, as defined by the degree of balance in sympathetic and vagusnerve activity.

The time interval between intrinsic ventricular heart contractionschanges in response to the body's metabolic need for a change in heartrate and the amount of blood pumped through the circulatory system. Forexample, during a period of exercise or other activity, a person'sintrinsic heart rate will generally increase over a time period ofseveral or many heartbeats. However, even on a beat-to-beat basis, thatis, from one heart beat to the next, and without exercise, the timeinterval between intrinsic heart contractions varies in a normal person.These beat-to-beat variations in intrinsic heart rate are the result ofproper regulation by the autonomic nervous system of blood pressure andcardiac output; the absence of such variations indicates a possibledeficiency in the regulation being provided by the autonomic nervoussystem. One method for analyzing HRV involves detecting intrinsicventricular contractions, and recording the time intervals between thesecontractions, referred to as the R-R intervals, after filtering out anyectopic contractions (ventricular contractions that are not the resultof a normal sinus rhythm). This signal of R-R intervals is typicallytransformed into the frequency-domain, such as by using fast Fouriertransform (“FFT”) techniques, so that its spectral frequency componentscan be analyzed and divided into low and high frequency bands. Forexample, the low frequency (LF) band can correspond to a frequency (“f”)range 0.04 Hz≦f<0.15 Hz, and the high frequency (HF) band can correspondto a frequency range 0.15 Hz≦f≦0.40 Hz. The HF band of the R-R intervalsignal is influenced only by the parasympathetic/vagal component of theautonomic nervous system. The LF band of the R-R interval signal isinfluenced by both the sympathetic and parasympathetic components of theautonomic nervous system. Consequently, the ratio LF/HF is regarded as agood indication of the autonomic balance between sympathetic andparasympathetic/vagal components of the autonomic nervous system. Anincrease in the LF/HF ratio indicates an increased predominance of thesympathetic component, and a decrease in the LF/HF ratio indicates anincreased predominance of the parasympathetic component. For aparticular heart rate, the LF/HF ratio is regarded as an indication ofpatient wellness, with a lower LF/HF ratio indicating a more positivestate of cardiovascular health. A spectral analysis of the frequencycomponents of the R-R interval signal can be performed using a FFT (orother parametric transformation, such as autoregression) technique fromthe time domain into the frequency domain. Such calculations requiresignificant amounts of data storage and processing capabilities.Additionally, such transformation calculations increase powerconsumption, and shorten the time during which the implantedbattery-powered device can be used before its replacement is required.

One example of an HRV parameter is SDANN (standard deviation of averagedNN intervals), which represents the standard deviation of the means ofall the successive 5 minutes segments contained in a whole recording.Other HRV parameters can be used.

HRT

Heart rate turbulence (HRT) is the physiological response of the sinusnode to a premature ventricular contraction (PVC), consisting of a shortinitial heart rate acceleration followed by a heart rate deceleration.HRT has been shown to be an index of autonomic function, closelycorrelated to HRV. HRT is believed to be an autonomic baroreflex. ThePVC causes a brief disturbance of the arterial blood pressure (lowamplitude of the premature beat, high amplitude of the ensuing normalbeat). This fleeting change is registered immediately with aninstantaneous response in the form of HRT if the autonomic system ishealthy, but is either weakened or missing if the autonomic system isimpaired.

By way of example and not limitation, it has been proposed to quantifyHRT using Turbulence Onset (TO) and Turbulence Slope (TS). TO refers tothe difference between the heart rate immediately before and after aPVC, and can be expressed as a percentage. For example, if two beats areevaluated before and after the PVC, TO can be expressed as:

${{TO}\mspace{14mu}\%} = {\frac{\left( {{RR}_{+ 1} + {RR}_{+ 2}} \right) - \left( {{RR}_{- 2} + {RR}_{- 1}} \right)}{\left( {{RR}_{- 2} + {RR}_{- 1}} \right)}*100.}$RR⁻² and RR⁻¹ are the first two normal intervals preceding the PVC andRR₊₁ and RR₊₂ are the first two normal intervals following the PVC. Invarious embodiments, TO is determined for each individual PVC, and thenthe average value of all individual measurements is determined. However,TO does not have to be averaged over many measurements, but can be basedon one PVC event. Positive TO values indicate deceleration of the sinusrhythm, and negative values indicate acceleration of the sinus rhythm.The number of R-R intervals analyzed before and after the PVC can beadjusted according to a desired application. TS, for example, can becalculated as the steepest slope of linear regression for each sequenceof five R-R intervals. In various embodiments, the TS calculations arebased on the averaged tachogram and expressed in milliseconds per RRinterval. However, TS can be determined without averaging. The number ofR-R intervals in a sequence used to determine a linear regression in theTS calculation also can be adjusted according to a desired application.

Rules or criteria can be provided for use to select PVCs and for use inselecting valid RR intervals before and after the PVCs. A PVC event canbe defined by an R-R interval in some interval range that is shorterthan a previous interval by some time or percentage, or it can bedefined by an R-R interval without an intervening P-wave (atrial event)if the atrial events are measured. Various embodiments select PVCs onlyif the contraction occurs at a certain range from the precedingcontraction and if the contraction occurs within a certain range from asubsequent contraction. For example, various embodiments limit the HRTcalculations to PVCs with a minimum prematurity of 20% and apost-extrasystole interval which is at least 20% longer than the normalinterval. Additionally, pre-PVC R-R and post-PVC R-R intervals areconsidered to be valid if they satisfy the condition that none of thebeats are PVCs. One HRT process, for example, excludes RR intervals thatare less than a first time duration, that are longer than a second timeduration, that differ from a preceding interval by more than a thirdtime duration, or that differ from a reference interval by apredetermined amount time duration or percentage. In an embodiment ofsuch an HRT process with specific values, RR intervals are excluded ifthey are less than 300 ms, are more than 2000 ms, differ from apreceding interval by more than 200 ms, or differ by more than 20% fromthe mean of the last five sinus intervals. Various embodiments of thepresent subject matter provide programmable parameters, such as any ofthe parameters identified above, for use in selecting PVCs and for usein selecting valid RR intervals before and after the PVCs.

The neural stimulation device that incorporates this technique forassessing autonomic balance can be used to provide eitherparasympathetic stimulation or inhibition or sympathetic stimulation orinhibition. Various device embodiments include means for pacing aventricle, such as at least one ventricular pacing lead. To measureautonomic balance for closed-loop therapy titration, the deviceintermittently introduces or senses a PVC, and measures the resultingheart rate turbulence, as described above.

Benefits of using HRT to monitor autonomic balance include the abilityto measure autonomic balance at a single moment in time. Additionally,unlike the measurement of HRV, HRT assessment can be performed inpatients with frequent atrial pacing. Further, HRT analysis provides fora simple, non-processor-intensive measurement of autonomic balance.Thus, data processing, data storage, and data flow are relatively small,resulting in a device with less cost and less power consumption. Also,HRT assessment is faster than HRV, requiring much less R-R data. HRTallows assessment over short recording periods similar in duration totypical neural stimulation burst durations, such as on the order of tensof seconds, for example.

Heart Sounds

Distinguishable heart sounds include the following four heart sounds.The first heart sound (S₁), is initiated at the onset of ventricularsystole and consists of a series of vibrations of mixed, unrelated, lowfrequencies. It is the loudest and longest of the heart sounds, has adecrescendo quality, and is heard best over the apical region of theheart. The tricuspid valve sounds are heard best in the fifthintercostal space, just to the left of the sternum, and the mitralsounds are heard best in the fifth intercostal space at the cardiacapex. S₁ is chiefly caused by oscillation of blood in the ventricularchambers and vibration of the chamber walls. The vibrations areengendered by the abrupt rise of ventricular pressure with accelerationof blood back toward the atria, and the sudden tension and recoil of theA-V valves and adjacent structures with deceleration of the blood by theclosed A-V valves. The vibrations of the ventricles and the containedblood are transmitted through surrounding tissue and reach the chestwall where they may be heard or recorded. The intensity of S₁ isprimarily a function of the force of the ventricular contraction, butalso of the interval between atrial and ventricular systoles. If the A-Vvalve leaflets are not closed prior to ventricular systole, greatervelocity is imparted to the blood moving toward the atria by the timethe A-V valves are snapped shut by the rising ventricular pressure, andstronger vibrations result from this abrupt deceleration of the blood bythe closed A-V valves.

The second heart sound (S₂), which occurs on closure of the semi-lunarvalves, is composed of higher frequency vibrations, is of shorterduration and lower intensity, and has a more “snapping” quality than thefirst heart sound. The second sound is caused by abrupt closure of thesemi-lunar valves, which initiates oscillations of the columns of bloodand the tensed vessel walls by the stretch and recoil of the closedvalve. Conditions that bring about a more rapid closure of thesemi-lunar valve, such as increases in pulmonary artery or aortapressure (e.g., pulmonary or systemic hypertension), will increase theintensity of the second heart sound. In the adult, the aortic valvesound is usually louder than the pulmonic, but in cases of pulmonaryhypertension, the reverse is often true.

The third heart sound (S₃), which is more frequently heard in childrenwith thin chest walls or in patients with rapid filling wave due to leftventricular failure, consists of a few low intensity, low-frequencyvibrations. It occurs in early diastole and is believed to be due tovibrations of the ventricular walls caused by abrupt acceleration anddeceleration of blood entering the ventricles on opening of the atrialventricular valves. A fourth or atrial sound (S₄), consisting of a fewlow-frequency oscillations, is occasionally heard in normal individuals.It is caused by oscillation of blood and cardiac chambers created byatrial contraction. Accentuated S₃ and S₄ sounds may be indicative ofcertain abnormal conditions and are of diagnostic significance.

Thus, a heart sound can be used in determining a heart failure status.For example, a more severe HF status tends to be reflected in a largerS₃ amplitude.

Electrograms

Example of ECG features that can be extracted to provide an indicator ofHF status include a QRS complex duration due to left bundle branchblock, ST segment deviation, and a Q wave due to myocardial infarction.Any one or combination of these features can be used to provide theindicator of HF status. Other features can be extracted from the ECG.

Activity

Activity sensors can be used to assess the activity of the patient.Sympathetic activity naturally increases in an active patient, anddecreases in an inactive patient. Thus, activity sensors can provide acontextual measurement for use in determining the autonomic balance ofthe patient, and thus the HF status of the patient. Various embodiments,for example, provide a combination of sensors to trend heart rate and/orrespiration rate to provide an indicator of activity.

Respiration

Two methods for detecting respiration involve measuring a transthoracicimpedance and minute ventilation. Respiration can be an indicator ofactivity, and can provide an explanation of increased sympathetic tonethat does not directly related to a HF status. For example, it may notbe appropriate to change a HF therapy due to a detected increase insympathetic activity attributable to exercise.

Respiration measurements (e.g. transthoracic impedance) can also be usedto measure Respiratory Sinus Arrhythmia (RSA). RSA is the natural cycleof arrhythmia that occurs through the influence of breathing on the flowof sympathetic and vagus impulses to the sinoatrial node. The rhythm ofthe heart is primarily under the control of the vagus nerve, whichinhibits heart rate and the force of contraction. The vagus nerveactivity is impeded and heart rate begins to increase when a breath isinhaled. When exhaled, vagus nerve activity increases and the heart ratebegins to decrease. The degree of fluctuation in heart rate is alsocontrolled significantly by regular impulses from the baroreceptors(pressure sensors) in the aorta and carotid arteries. Thus, ameasurement of autonomic balance can be provided by correlating heartrate to the respiration cycle.

Pulmonary Artery Pressure

As identified above, high blood pressure can contribute to heartfailure. Chronically high blood pressure, or a chronic blood pressurethat trends higher, provides an indication of an increased likelihood ofheart failure. Various embodiments use pulmonary artery pressure toapproximate filling pressure. Filling pressure is a marker of preload,and preload is an indicator of heart failure status.

HF Status Index

Embodiments of the present subject matter provide a HF status indexusing two or more HF parameters, such as any two or more of the HFparameters identified above. The index reduces the false positives, andthus reduces power drain associated with unneeded therapy and alsoreduces the risk of overstimulation for the patient. Embodiments of theindex include a composite index, where each HF parameters used as aninput is appropriately weighted to generated the composite index. Forexample, index can be provided by (parameter 1)*A+(parameter 2)*B. Inanother example, index includes a product of the parameters (e.g.(parameter 1)*(parameter 2)), or can include on parameter divided byanother (e.g. (parameter 1)/(parameter 2)). Other algorithms can be usedto create an index from the two or more parameters.

Other examples of creating an index based on two or more HF-relatedparameters to control a therapy are provided below. These examplesinclude the use of statistical probabilities and the use of anintelligent system to determine a HF status based on two or more HFparameters.

Statistical Probabilities

U.S. application Ser. No. 11/276,735, filed Mar. 13, 2006, issued asU.S. Pat. No. 7,713,213, and entitled “Physiological Event DetectionSystems and Methods,” which is incorporated by reference, discusses theproblems of false positives using probability densities. FIG. 1A showsan example of a probability density function p_(i)(x|H₀) based uponmeasurements taken over a period time for a physiological parameter(e.g., heart sound amplitude, heart rate and the like) of a patient. Theillustrated function p_(i)(x|H₀) shows a distribution for non-event(baseline) measurements taken for the physiological parameter, and thusrepresents a distribution of measurements for a stable patient. Thesemeasurements statistically characterize the non-event environment of thepatient (i.e., no heart failure, arrhythmia, and the like). Theprobability density function p_(i)(x|H₁) shown in dashed lines in FIG.1A, illustrates an estimated distribution of measurements for aphysiological parameter representative of an “event” condition (e.g.,heart failure and the like). Because event measurements are typicallyrare, the function p_(i)(x|H₁) typically only approximates thedistribution of event-related measurements. H₁ thereby is the hypothesisshowing events of significance. In another example, H₁ is estimated froma population of past events. As shown in FIG. 1A and further describedbelow, outlier measurements of the physiological parameter that approachthe event distribution p_(i)(x|H₁) are less likely to be a false alarm(i.e., decreased probability of not being indicative of an event), andconversely an increased probability of being indicative of an event(e.g., heart failure, arrhythmia and the like). Conceptually,measurements that are outliers for p_(i)(x|H₀) more closely resembleevent measurements than non-event measurements.

In various embodiments, the probability density function p_(i)(x|H₀) isgenerated using a histogram of actual measured values. The actualmeasured values are used to directly estimate the probability densityfunction. Properties of the measurements (e.g., median and percentilemeasure) are used to create the probability density function. In variousembodiments, a particular probability distribution is used, such as aGaussian distribution or other function that is specified mathematically(e.g., by estimating the mean and standard deviation) or otherwise. Invarious embodiments, the probability density function is generated bycurve-fitting over histogram data. The measurements used to generate theprobability density function p_(i)(x|H₀) are collected and stored.

In certain examples, particular measurements are excluded from use incomputing the probability density function p(x_(i)|H₀), such ascorrupted measurements, old measurements, event-related measurements—thefunction p_(i)(x|H₀) should only include non-event data—and the like. Inone example, the probability distribution function is generated withmeasurements taken during a particular (e.g., moving) window of time. Incertain examples, the moving window of time extends a specified intervalback from the time of the most recent measurement of the physiologicalparameter. In certain examples, older measurements outside of the movingwindow of time are excluded from use in computing the probabilitydistribution function. This allows the probability distribution functionto update and follow gradual drifts in the physiological parameter byusing the most recent measurements. Older measurements can be stored inthe implantable medical device and/or external system, such as forhistorical use. Additionally, where measurements are determined toindicate an event, as described below, such event-related measurementsare flagged and excluded from use in generating the non-eventprobability distribution function.

In certain examples, measurements that are deemed unreliable orcorrupted are not used to compute the non-event probability distributionfunction. For example, certain physiological parameters are confoundedby other effects. For example, heart sounds may be affected by posture.A second sensor (e.g., a posture detector) can be used to detect postureto “qualify” the heart sounds data, such that only heart soundsassociated with a particular posture are used to compute a particularprobability distribution function—or different probability distributionfunctions can be computed for various postures. Similarly, certainphysiological parameters are affected by sleep state, such thatmeasurements generated during periods of rest, such as sleep, may varyfrom measurements taken during waking hours. In this example, a sleepdetector may be used to qualify the primary physiological parameteraccording to a particular sleep state. Activity can also affect sensedphysiological parameters. In general, one or more secondaryphysiological sensors can be used to qualify data from a primaryphysiological sensor to remove unreliable or corrupted data from use incomputing the probability distribution function, which is also useful ina situation in which the primary physiological sensor fails. Thus,according to the present subject matter, two or more sensors can be usedto create an index for a HF status, such as may be presented by thenon-event probability distribution function.

FIG. 1B shows one example of the non-event probability density functionp_(i) (x═H₀). As described above, the function p_(i)(x|H₀) is typicallyderived from non-event measurements taken by a sensor of a physiologicalparameter for the patient. A measurement, such as an instant measurementx_(i)=k can be plotted along the probability density functionp_(i)(x|H₀) and a confidence is derived by integrating the tail areabased on the following equation:

C_(i) = ∫_(k)^(∞)p_(i)(x|H₀)𝕕xThe confidence C_(i) is proportional to the instantaneous probabilitythe measurement k is a false alarm (i.e., a non-event measurement).Integration of the probability density function p_(i)(x|H₀) tail areafrom the measurement k toward the end of the distribution therebydetermines the instantaneous probability that k is a false alarm. Ameasurement that approaches the end of the distribution has a decreasedprobability that it indicates a false alarm. It is conversely moreprobable that such a measurement is indicative of an event, such as theonset of an abnormal condition (e.g., heart failure). The measurement kis typically an existing measurement already recorded.

FIG. 1C shows another example, in which a function p_(j)(x|H₀) isrepresented by a negative-tailed distribution of measurements for aphysiological parameter. One example of a physiological parameter havinga negative-tailed distribution is near-DC thoracic impedance. Generally,depressed DC thoracic impedance measurements (e.g., intrathoracic totalimpedance) indicate fluid accumulation, which may be associated withpulmonary edema. Therefore, such depressed DC thoracic impedancemeasurements represent a decreased probability of false alarm in apulmonary edema detection scheme. Like the function p_(i)(x|H₀),function p_(j)(x|H₀) is typically derived from non-event measurementstaken by a sensor of a physiological parameter for the patient. Ameasurement, such as an instant measurement x_(j)=1 can be plotted alongthe probability density function p_(j)(x|H₀) and a confidence is derivedby integrating the tail area based on the following equation:

C_(j) = ∫_(k)^(l)p_(j)(x|H₀)𝕕xThe confidence C_(j) is proportional to the instantaneous probabilitythe measurement 1 is a false alarm (i.e., a non-event measurement).Integration of the probability density function p_(j)(x|H₀) tail areafrom the measurement 1 toward the left end of the distributiondetermines the instantaneous probability that 1 is a false alarm. Aswith the function p_(i)(x|H₀), a measurement that approaches the end ofthe distribution, has a decreased instantaneous probability that itindicates a false alarm, and it is conversely more probable that themeasurement is indicative of an event, such as the onset of a condition(e.g., heart failure). Optionally, the value corresponding to the “end”of the distribution need not occur +/− infinity, but can instead beapproximated using the estimated end of the distribution (e.g., anapproximated value approaching a measured end of the distribution, anactual measured value, a value approaching +/− infinity and the like).

In certain examples, the clinician sets a threshold based on a constantspecified false alarm rate (FAR) (i.e., constant false alarm rate). Forexample, the physician can specify that the threshold should beautomatically set such that it yields false alarms approximately 5%(0.05) of the time. This specified FAR is independent of anystatistical-based analysis of the distribution for a physiologicalparameter and thereby independent of any influence from thedistribution. From the clinician-specified FAR, a threshold can beautomatically determined, such as to compare against the valuescorresponding to the confidences generated with equations, such as thoseshown for C_(i) and C_(j). If the values corresponding to theconfidences exceed the FAR-based threshold, then, in certain examples, atherapy is provided in response to the detected physiological event. Inone example, the threshold is a value proportional to a specificitydesired by the clinician. For instance, in a situation where the patientis susceptible to a condition (e.g., has shown precursor symptoms, has ahistory of condition and the like) the clinician would likely set a lowthreshold to ensure that a patient at higher risk of the condition isprovided therapy. In another example, where the patient is unlikely toexperience the condition (e.g., the patient has a combinationpacemaker/defibrillator, but is not expected to experience heartfailure) the clinician would set a high threshold to ensure that the lowrisk patient is only treated if measurements indicate there is a highinstantaneous probability of the onset of the condition.

Intelligent System

U.S. Published Patent Application 20060010090, incorporated by referenceherein, provides an example of an intelligent system that providesremote monitoring of patients in an ambulatory setting using data from acombination of implantable and external sensors. In various embodiments,a variety of sensor signals are continuously monitored and the data iscollected in real time. The data, in one example, is processed by theintelligent system and upon certain conditions, a therapy is titratedand/or an alert notification is sent to a physician or a patient.

A combination of sensors provide chronic patient data under variousconditions and measured in various manners. For example, a combinationof sensor data is used to detect the patient's hemodynamic state andfacilitate assessment of congestion, perfusion, contractility or variousother conditions. In various embodiments, heart failure or otherconditions are assessed.

In one example, the system includes an inference engine which assemblesthe information coming from different sources and provides a concisesummary of heart failure, also referred to herein as a heart failureindex. The different sources, in various examples, includes implantablesensors as well as external sensors.

FIG. 2 illustrates system 200 having a plurality of data sources 201 ofparameters related to heart failure coupled to an intelligent system202. The data sources 201 include but are not limited to, for example,input devices such as implantable sensor 203, external sensor 204,physician input 205, patient input 206, patient history 207,pharmaceutical database 208 and population/clinical study data 209.

The implantable sensor 203, in various embodiments, includes one or moreimplantable sensors, such as a transthoracic impedance sensor, a minuteventilation sensor, a respiratory rate sensor, a heart monitor, anaccelerometer, an intracardiac pressure sensor, sensors for measuringHRV, sensors for measuring HRT, and other types of sensors.

The external sensor 204 includes one or more external, ornon-implantable sensors, examples of which include a weighing scale(mass sensor), a blood pressure cuff (or pressure sensor), an externalmonitor as well as other types of ambulatory sensors. In one example,external sensor 204 includes a weighing scale which may include adigital communication link with the intelligent system 202 or which mayprovide data that is manually entered into a personal digital assistant(PDA) or otherwise provided to the intelligent system 202.

The physician input 205 includes an interface or data entry deviceaccessible to a physician, medical personal or other user. Data enteredby the physician includes, for example, prescription information,medical records, patient symptoms, observation data as well as otherinformation. In one example, the physician input can be used to specifya particular value or threshold of a parameter. The physician input, inone example, allows entry of physician-established rules for performanceof the system.

The patient input 206 includes an interface or data entry deviceaccessible to a patient, a proxy for the patient or other user. Usingpatient input, a user is able to enter data corresponding to real timeor earlier observations. In one example, the patient input allows thepatient to enter data such as food intake, exercise activity, perceivedsensations and symptoms and other noted phenomena.

The patient history 207 includes an interface configured to receiveinformation including, for example, electronic medical records (EMR),clinical information system (CIS) data, or other data corresponding to aparticular patient. The data can include family medical history, patientvital signs, trends and other historical medical and clinical data.

The pharmaceutical database 208 includes data correlating specific drugswith medical conditions and symptoms. In various embodiments, thepharmaceutical database includes data generated based on researchcorresponding to specific geographical regions of the world, including,for example, the United States. The pharmaceutical database alsoincludes data indicating population pharmaco-kinetics for differentdrugs. Data included, for example, correlates the effects of a drug as afunction of time after having taken the drug. In various embodiments,the pharmaceutical database includes data about the drug therapy for aparticular patient.

The population/clinical study data 209 includes data indicatingrelationships between selected drugs, for example. In one example, thepopulation/clinical study data includes normative and statistical datashowing relationships between populations and particular drugs. In oneexample, the population/clinical study data includes data derived fromclinical studies data for a particular population.

The intelligent system 202 includes an inference engine and isimplemented, in various examples, in hardware or software. In oneexample, the intelligent system includes a processor executing an expertsystem algorithm stored in a memory. The intelligent system isconfigured to generate an inference based on the knowledge base and themeasured input signals. Examples of inference engines include a causalprobabilistic network such as a Bayesian network, fuzzy logic, adecision tree, a neural network or a self-organized map. In variousembodiments, the intelligent system 202 operates on the basis ofmeasured inputs and generates a knowledge base over a period of time.

A Bayesian network includes a conditional probability-based network thatrelies on Bayes theorem to characterize likelihood of different outcomesbased on known prior probabilities (i.e. observed prevalence of adisease) and newly acquired information (i.e. sensor signals). Bayesiannetworks use causal knowledge and explicitly model probabilisticdependence and independence relationships between different events.

Fuzzy logic provides a mechanism for manipulating uncertain informationand variables that do not otherwise permit simple categorization asaffirmative or negative. Fuzzy logic describes the application ofif-then rules to uncertain information and provides probability ofoutcomes based on preceding events or conditions. Fuzzy logic relies onprobabilistic if-then rules. According to principles of fuzzy logic, theprobability that a premise will be true is predictable, and theconclusion that follows will also occur with some probability.

A decision tree provides a method for representing multiple temporal andlogical inputs and the possible outcomes based on a combination of thoseinputs. A decision tree does not entail probabilities associated withbranches.

A neural network is a black-box information-processing device having anumber of non-linear processing modules connected together by elementsthat have information storage and programming functions. Aself-organized map is a particular type sheet-like neural network arrayconfigured to execute an adaptive algorithm capable of learning. Theneural network is based on the competitive and unsupervised learningprocess. Other types of expert systems are also contemplated.

One or more of the sensors 203 and 204 are used to provide a sensed HFstatus 210. The intelligent system 202 generates an inference (e.g. HFstatus index) based on a combination of information received from datasources 201. The HF status index is used to control the neuralstimulation 211 to the HF therapy neural targets 212. The informationderived from the data sources 201 is subject to errors and other sourcesof imprecision. In one example, the information is expressed usingprobabilities to quantify the uncertainty. For example, data derivedfrom a clinical study might indicate that if a particular level of aparameter is noted, then with a specified level of confidence, thepatient is suffering from a particular malady. Data from additionalsources will further modify the confidence level of the particularconclusion and further enhance the precision of an identification. Inone example, the intelligent system incorporates temporal reasoning forevents that have a time lag. For example, information about an eventincludes a temporal stamp and the time intervals between dependentevents is propagated through the network and is marked as a possiblecause of a later event.

Therapies

Neural Stimulation Therapies

Examples of neural stimulation therapies include neural stimulationtherapies

for heart failure, for blood pressure control such as to treathypertension, for respiratory problems such a sleep disorderedbreathing, for cardiac rhythm management, for myocardial infarction andischemia, for epilepsy, for depression, for pain, for migraines, foreating disorders and obesity, and for movement disorders. This listingof other neural stimulation therapies is not intended to be anexhaustive listing.

FIGS. 3A-3C illustrate that neural stimulation is effective as a HFtherapy. As reflected in FIGS. 3A and 3B, neural stimulation reduces orprevents an increase in the end diastolic area and the end systolic areacompared to a control group, and appears to reduce the end diastolicarea and end systolic area. As reflected in FIG. 3C, neural stimulationcorresponds to higher fractional shortening compared to a control group.Fractional shortening (FS) is a measure of left ventricular function,and can be calculated as:

${{FS} = {\frac{{EDD} - {ESD}}{EDD}*100\%}},$where EDD is the LV End Diastolic Dimension and ESD is the LV EndSystolic Dimension.Ventricular Remodeling

One therapy involves preventing and/or treating ventricular remodeling.Activity of the autonomic nervous system is at least partly responsiblefor the ventricular remodeling which occurs as a consequence of an MI ordue to heart failure. It has been demonstrated that remodeling can beaffected by pharmacological intervention with the use of, for example,ACE inhibitors and beta-blockers. Pharmacological treatment carries withit the risk of side effects, however, and it is also difficult tomodulate the effects of drugs in a precise manner. Another issue withdrug therapy is patient non-compliance. Embodiments of the presentsubject matter employ electrostimulatory means to modulate autonomicactivity, referred to as anti-remodeling therapy or ART. When deliveredin conjunction with ventricular resynchronization pacing, also referredto as remodeling control therapy (RCT), such modulation of autonomicactivity acts synergistically to reverse or prevent cardiac remodeling.

Increased sympathetic nervous system activity following ischemia oftenresults in increased exposure of the myocardium to epinephrine andnorepinephrine. These catecholamines activate intracellular pathwayswithin the myocytes, which lead to myocardial death and fibrosis.Stimulation of the parasympathetic nerves (vagus) inhibits this effect.According to various embodiments, the present subject matter selectivelyactivates the vagal cardiac nerves in addition to CRT in heart failurepatients to protect the myocardium from further remodeling andarrhythmogenesis. Other potential benefits of stimulating vagal cardiacnerves in addition to CRT include reducing inflammatory responsefollowing myocardial infarction, and reducing the electrical stimulationthreshold for defibrillating. For example, when a ventriculartachycardia is sensed, vagal nerve stimulation is applied, and then adefibrillation shock is applied. The vagal nerve stimulation allows thedefibrillation shock to be applied at less energy. Also, parasympatheticstimulation may terminate an arrhythmia or otherwise increase theeffectiveness of an anti-arrhythmia treatment.

As illustrated in FIGS. 4A and 4B, the heart 413 includes a superiorvena cava 414, an aortic arch 415, and a pulmonary artery 416. CRM leads417 pass nerve sites that can be stimulated in accordance with thepresent subject matter. FIG. 4A illustrates transvascularly fed leads,and FIG. 4B illustrates epicardial leads. Examples of electrodepositions are provided in the drawings by the symbol “X”. For example,CRM leads are capable of being intravascularly inserted through aperipheral vein and into the coronary sinus, and are capable of beingintravascularly inserted through a peripheral vein and through thetricuspid valve into the right ventricle of the heart (not expresslyshown in the figure) similar to a cardiac pacemaker lead, and continuefrom the right ventricle through the pulmonary valve into the pulmonaryartery. The coronary sinus and pulmonary artery are provided as examplesof vasculature proximate to the heart in which a lead can beintravascularly inserted to stimulate nerves within or proximate to thevasculature. Thus, according to various aspects of the present subjectmatter, nerves are stimulated in or around vasculature located proximateto the heart by at least one electrode intravascularly inserted therein.

FIGS. 5A and 5B illustrate the right side and left side of the heart,respectively, and further illustrate cardiac fat pads which provideneural targets for some neural stimulation therapies. FIG. 5Aillustrates the right atrium 518, right ventricle 519, sinoatrial node520, superior vena cava 514, inferior vena cava 521, aorta 522, rightpulmonary veins 523, and right pulmonary artery 524. FIG. 5A alsoillustrates a cardiac fat pad 525 between the superior vena cava andaorta. Neural targets in the cardiac fat pad 525 are stimulated in someembodiments using an electrode screwed into or otherwise placed in thefat pad, and are stimulated in some embodiments using anintravenously-fed lead proximately positioned to the fat pad in a vesselsuch as the right pulmonary artery or superior vena cava, for example.FIG. 5B illustrates the left atrium 526, left ventricle 527, rightatrium 518, right ventricle 519, superior vena cava 514, inferior venacava 521, aorta 522, right pulmonary veins 523, left pulmonary vein 528,right pulmonary artery 524, and coronary sinus 529. FIG. 5B alsoillustrates a cardiac fat pad 530 located proximate to the right cardiacveins and a cardiac fat pad 531 located proximate to the inferior venacava and left atrium. Neural targets in the fat pad 530 are stimulatedin some embodiments using an electrode screwed into the fat pad 530, andare stimulated in some embodiments using an intravenously-fed leadproximately positioned to the fat pad in a vessel such as the rightpulmonary artery 524 or right pulmonary vein 523, for example. Neuraltargets in the fat pad 531 are stimulated in some embodiments using anelectrode screwed into the fat pad 531, and are stimulated in someembodiments using an intravenously-fed lead proximately positioned tothe fat pad in a vessel such as the inferior vena cava 521 or coronarysinus or a lead in the left atrium 526, for example.

Various lead embodiments implement a number of designs, including anexpandable stent-like electrode with a mesh surface dimensioned to abuta wall of a predetermined blood vessel, a coiled electrode(s), a fixedscrew-type electrode(s), and the like. Various embodiments place theelectrode(s) inside the blood vessel, into the wall of the blood vessel,or a combination of at least one electrode inside the blood vessel andat least one electrode into the wall of the blood vessel. The neuralstimulation electrode(s) can be integrated into the same lead used forCRT or in another lead in addition to CRT lead(s).

Intravascularly-fed leads adapted to transvascularly stimulate a targetoutside of the vessel, also referred to herein as transvascular leads,can be used to stimulate other nerve sites. For example, an embodimentfeeds a transvascular stimulation lead into the right azygos vein tostimulate and/or inhibit nerve traffic on the vagus nerve; and anembodiment feeds a transvascular stimulation lead into the internaljugular vein to stimulate and/or inhibit nerve traffic on the vagusnerve. Various embodiments use at least one lead intravascularly fedalong a lead path to transvascularly apply neural stimulation andelectrically stimulate a cardiac muscle, such as ventricular pacing, aspart of CRT.

Other transvascular locations have been mentioned with respect to FIGS.5A and 5B. Depending on the intravascular location of the neuralstimulation electrode(s), the right vagal branch, the left vagal branchor a combination of the right and left vagal branches are capable ofbeing stimulated. The left and right vagal branches innervate differentareas of the heart, and thus provide different results when stimulated.According to present knowledge, the right vagus nerve appears toinnervate the right side of the heart, including the right atrium andright ventricle, and the left vagus nerve appears to innervate the leftside of the heart, including the left atrium and left ventricle.Stimulation of the right vagus has more chronotropic effects because thesinus node is on the right side of the heart. Thus, various embodimentsselectively stimulate the right vagus nerve and/or the left vagus nerveto selectively control contractility, excitability, and inflammatoryresponse on the right and/or left side of the heart. Since the venoussystem is for the most part symmetrical, leads can be fed into anappropriate vessel to transvascularly stimulate the right or left vagusnerve. For example, a lead in the right internal jugular vein can beused to stimulate the right vagus nerve and a lead in the left internaljugular vein can be used to stimulate the left vagus nerve.

The stimulation electrode(s) are not in direct neural contact with thenerve when the transvascular approach to peripheral nerve stimulation isused. Thus, problems associated with neural inflammation and injurycommonly associated with direct contact electrodes are reduced.

Hypertension

As discussed above, hypertension can contribute to heart failure. Oneneural stimulation therapy involves treating hypertension by stimulatingthe baroreflex for sustained periods of time sufficient to reducehypertension. The baroreflex is a reflex that can be triggered bystimulation of a baroreceptor or an afferent nerve trunk. Baroreflexneural targets include any sensor of pressure changes, such as sensorynerve endings in the wall of the auricles of the heart, cardiac fatpads, vena cava, aortic arch and carotid sinus, that is sensitive tostretching of the wall resulting from increased pressure from within,and that functions as the receptor of the central reflex mechanism thattends to reduce that pressure. Examples of afferent nerve trunks thatcan serve as baroreflex neural targets include the vagus, aortic andcarotid nerves. Stimulating baroreceptors inhibits sympathetic nerveactivity (stimulates the parasympathetic nervous system) and reducessystemic arterial pressure by decreasing peripheral vascular resistanceand cardiac contractility. Baroreceptors are naturally stimulated byinternal pressure and the stretching of the arterial wall. Some aspectsof the present subject matter locally stimulate specific nerve endingsin arterial walls rather than stimulate afferent nerve trunks in aneffort to stimulate a desire response (e.g. reduced hypertension) whilereducing the undesired effects of indiscriminate stimulation of thenervous system. For example, some embodiments stimulate baroreceptorsites in the pulmonary artery. Some embodiments of the present subjectmatter involve stimulating either baroreceptor sites or nerve endings inthe aorta, the chambers of the heart, the fat pads of the heart, andsome embodiments of the present subject matter involve stimulating anafferent nerve trunk, such as the vagus, carotid and aortic nerves. Someembodiments stimulate afferent nerve trunks using a cuff electrode, andsome embodiments stimulate afferent nerve trunks using an intravascularlead positioned in a blood vessel proximate to the nerve, such that theelectrical stimulation passes through the vessel wall to stimulate theafferent nerve trunk.

Myocardial Stimulation Therapies

Various embodiments use HF status as feedback for a myocardialstimulation therapy. For example, some embodiments provide or adjust CRTin response to a HF status index. Various embodiments also include orintegrate myocardial stimulation with neural stimulation therapies. Someof these myocardial therapies are discussed below.

Bradycardia Pacing/CRT Pacing

A pacemaker is a device which paces the heart with timed pacing pulses,most commonly for the treatment of bradycardia where the ventricularrate is too slow. Atrio-ventricular conduction defects (i.e., AV block)and sick sinus syndrome represent the most common causes of bradycardiafor which permanent pacing may be indicated. If functioning properly,the pacemaker makes up for the heart's inability to pace itself at anappropriate rhythm in order to meet metabolic demand by enforcing aminimum heart rate.

Implantable devices have also been developed that affect the manner anddegree to which the heart chambers contract during a cardiac cycle inorder to promote the efficient pumping of blood. The heart pumps moreeffectively when the chambers contract in a coordinated manner, a resultnormally provided by the specialized conduction pathways in both theatria and the ventricles that enable the rapid conduction of excitation(i.e., depolarization) throughout the myocardium. These pathways conductexcitatory impulses from the sino-atrial node to the atrial myocardium,to the atrio-ventricular node, and thence to the ventricular myocardiumto result in a coordinated contraction of both atria and bothventricles. This both synchronizes the contractions of the muscle fibersof each chamber and synchronizes the contraction of each atrium orventricle with the contralateral atrium or ventricle. Without thesynchronization afforded by the normally functioning specializedconduction pathways, the heart's pumping efficiency is greatlydiminished. Pathology of these conduction pathways and otherinter-ventricular or intra-ventricular conduction deficits can be acausative factor in heart failure, which refers to a clinical syndromein which an abnormality of cardiac function causes cardiac output tofall below a level adequate to meet the metabolic demand of peripheraltissues. In order to treat these problems, implantable cardiac deviceshave been developed that provide appropriately timed electricalstimulation to one or more heart chambers in an attempt to improve thecoordination of atrial and/or ventricular contractions, termed cardiacresynchronization therapy (CRT). Ventricular resynchronization is usefulin treating heart failure because, although not directly inotropic,resynchronization can result in a more coordinated contraction of theventricles with improved pumping efficiency and increased cardiacoutput. Currently, a common form of CRT applies stimulation pulses toboth ventricles, either simultaneously or separated by a specifiedbiventricular offset interval, and after a specified atrio-ventriculardelay interval with respect to the detection of an intrinsic atrialcontraction or delivery of an atrial pace.

Anti-Tachycardia Therapy

Cardioversion, an electrical shock delivered to the heart synchronouslywith the QRS complex, and defibrillation, an electrical shock deliveredwithout synchronization to the QRS complex, can be used to terminatemost tachyarrhythmias. The electric shock terminates the tachyarrhythmiaby simultaneously depolarizing the myocardium and rendering itrefractory. A class of CRM devices known as an implantable cardioverterdefibrillator (ICD) provides this kind of therapy by delivering a shockpulse to the heart when the device detects tachyarrhythmias. Anothertype of electrical therapy for tachycardia is anti-tachycardia pacing(ATP). In ventricular ATP, the ventricles are competitively paced withone or more pacing pulses in an effort to interrupt the reentrantcircuit causing the tachycardia. Modern ICDs typically have ATPcapability, and deliver ATP therapy or a shock pulse when atachyarrhythmia is detected.

Therapy for Cardiac Remodeling

CRT can be beneficial in reducing the deleterious ventricular remodelingwhich can occur in post-MI and heart failure patients. Presumably, thisoccurs as a result of changes in the distribution of wall stressexperienced by the ventricles during the cardiac pumping cycle when CRTis applied. The degree to which a heart muscle fiber is stretched beforeit contracts is termed the preload, and the maximum tension and velocityof shortening of a muscle fiber increases with increasing preload. Whena myocardial region contracts late relative to other regions, thecontraction of those opposing regions stretches the later contractingregion and increases the preload. The degree of tension or stress on aheart muscle fiber as it contracts is termed the afterload. Becausepressure within the ventricles rises rapidly from a diastolic to asystolic value as blood is pumped out into the aorta and pulmonaryarteries, the part of the ventricle that first contracts due to anexcitatory stimulation pulse does so against a lower afterload than doesa part of the ventricle contracting later. Thus a myocardial regionwhich contracts later than other regions is subjected to both anincreased preload and afterload. This situation is created frequently bythe ventricular conduction delays associated with heart failure andventricular dysfunction due to an MI. The increased wall stress to thelate-activating myocardial regions is most probably the trigger forventricular remodeling. By pacing one or more sites in a ventricle in amanner which causes a more coordinated contraction, CRT providespre-excitation of myocardial regions which would otherwise be activatedlater during systole and experience increased wall stress. Thepre-excitation of the remodeled region relative to other regions unloadsthe region from mechanical stress and allows reversal or prevention ofremodeling to occur.

Device Embodiments

FIG. 6 illustrates a device embodiment to generate a sensed HF statusindex using two or more HF-related parameters and controlling neuralstimulation to an HF-therapy neural target. In the illustrated deviceembodiment, a number of HF-related parameters 632 are able to bemeasured. Examples include HRV 633, HRT 634, heart sounds 635, pulmonaryartery pressure 636 and/or other blood pressure, transthoracic impedance637 or other sensed parameter(s) 638. These measured HF-relatedparameters are received by an index generator 639, which generates asensed HF status index 640 as a function of at least two measuredparameters 632 or otherwise using at least two measured parameters 632.A comparator 641 compares the index 640 to a target 642 for the index.The target can be a programmed value. The result of the comparison isused to control the neural stimulation 643, which is applied to the HFtherapy neural target(s) 644. In various embodiments, the neuralstimulation can stimulate parasympathetic activity and/or inhibitsympathetic neural activity to elicit a parasympathetic response forchronic HF therapy. In various embodiments, the neural stimulation canstimulate sympathetic activity and/or inhibit parasympathetic activityto elicit a sympathetic response, such as may be desirable as a shortterm therapy in response to an event to maintain cardiac output untilthe patient can travel to a clinical setting.

FIG. 7 illustrates a device embodiment to generate a chronic orlong-term sensed HF status index and an acute or short-term sensed HFstatus index using two or more HF-related parameters, and controllingneural stimulation to an HF-therapy neural target using the indices.Measured HF-related parameters are received by a long-term indexgenerator 739A, which generates a long-term sensed HF status index 740Aas a function of at least two measured parameters 732 or otherwise usingat least two measured parameters 732. A comparator 741A compares theindex 740A to a target 742A for the index. The target can be aprogrammed value. In various embodiments, the target is based on anaverage or trend of a number of previous values for the index, such thatthe comparator is able to determine if the index value is trendinghigher or lower. The result of the comparison is used as chronicfeedback for the neural stimulation 743, which is applied to the HFtherapy neural target(s) 744. For example, the long-term HF status indexcan be used to adjust an intensity, duration or location of neuralstimulation to increase or decrease a parasympathetic response as partof a HF therapy. Measured HF-related parameters are received by ashort-term index generator 739B, which generates a short-term sensed HFstatus index 740B as a function of at least two measured parameters 732or otherwise using at least two measured parameters 732. A comparator741B compares the index 740B to a target 742B for the index. The targetcan be a programmed value. In various embodiments, the target is basedon an average or trend of a number of previous values for the index,such that the comparator is able to determine if the index value istrending higher or lower. The result of the comparison is used asshort-term feedback for the neural stimulation 743, which is applied tothe HF therapy neural target(s) 744. For example, the long-term HFstatus index can be used to adjust an intensity, duration or location ofneural stimulation to increase or decrease a sympathetic response aspart of an acute HF therapy due to a decompensation event.

FIG. 8 illustrates a method for controlling an HF therapy, according tovarious embodiments of the present subject matter. The device embodimentof FIG. 6, for example, is capable of performing this method. At 845, atleast two HF-related parameters are converted into a HF-status index. At846, the neural stimulation for a HF-therapy is controlled using theHF-status index and a target for the index.

FIG. 9 illustrates a method for controlling an HF therapy, according tovarious embodiments of the present subject matter. The device embodimentof FIG. 7, for example, is capable of performing this method. The boxes945 and 946 in FIG. 9 generally correspond to 845 and 846 in FIG. 8. At947, at least two HF-related parameters are converted into indexindicative of a short-term HF-status; and at 948, at least twoHF-related parameters are converted into index indicative of a long-termHF-status. At 949, the neural stimulation for a short-term HF-therapy iscontrolled using the short-term HF-status index and a target for theshort-term index; and at 950, the neural stimulation for a long-termHF-therapy is controlled using the long-term HF-status index and atarget for the long-term index. Short-term indexes can be based onrecent measured HF-related parameters, such as parameters measured inthe past minute or hour. Long-term indexes can be based on parametersmeasured over a longer period of time, such as hours, days, weeks andmonths, for example . . . FIG. 10 illustrates an implantable medicaldevice (IMD) 1051, according to various embodiments of the presentsubject matter. The illustrated IMD provides neural stimulation signalsfor delivery to predetermined neural targets to provide heart failuretherapy. The illustrated device includes controller circuitry 1052 andmemory 1053. The controller circuitry is capable of being implementedusing hardware, software, and combinations of hardware and software. Forexample, according to various embodiments, the controller circuitryincludes a processor to perform instructions embedded in the memory toperform functions associated with the neural stimulation therapy. Forexample, the illustrated device further includes a transceiver 1054 andassociated circuitry for use to communicate with a programmer or anotherexternal or internal device. Various embodiments have wirelesscommunication capabilities. For example, some transceiver embodimentsuse a telemetry coil to wirelessly communicate with a programmer oranother external or internal device.

The illustrated device further includes neural stimulation circuitry1055. Various embodiments of the device also includes sensor circuitry1056. According to some embodiments, one or more leads are able to beconnected to the sensor circuitry and neural stimulation circuitry. Someembodiments use wireless connections between the sensor(s) and sensorcircuitry, and some embodiments use wireless connections between thestimulator circuitry and electrodes. According to various embodiments,the neural stimulation circuitry is used to apply electrical stimulationpulses to desired neural targets, such as through one or morestimulation electrodes 1057 positioned at predetermined location(s).Some embodiments use transducers to provide other types of energy, suchas ultrasound, light or magnetic energy. In various embodiments, thesensor circuitry is used to detect physiological responses. Examples ofphysiological responses include cardiac activity, such as heart rate andminute ventilation, blood pressure, and respiration, such as tidalvolume and minute ventilation, as well as sensed HRV and HRT data. Thecontroller circuitry can compare a target range (or ranges) of thesensed physiological response(s) stored in the memory to the sensedphysiological response(s) to appropriately adjust the intensity of theneural stimulation/inhibition.

According to various embodiments, the stimulation circuitry 1055includes modules to set or adjust any one or any combination of two ormore of the following pulse features: the amplitude 1058 of thestimulation pulse, the frequency 1059 of the stimulation pulse, theburst frequency 1060 of the pulse, the wave morphology 1061 of thepulse, and the pulse width 1062. The illustrated burst frequency 1060pulse feature includes burst duration 1063 and duty cycle 1064, whichcan be adjusted as part of a burst frequency pulse feature or can beadjusted separately. For example, a burst frequency can refer to thenumber of bursts per minute. Each of these bursts has a burst duration(an amount of time bursts of stimulation are provided) and a duty cycle(a ratio of time where stimulation is provided to total time). Thus, byway of example and not limitation, six bursts can be delivered during aone minute stimulation time (burst duration), where the length (pulsewidth) of each burst is five seconds and the time period between burstsis five seconds. In this example, the burst frequency is six burst perminute, the burst duration is 60 seconds, and the duty cycle is 50% ((6bursts×5 sec./burst)/60 seconds). Additionally, the duration of one ormore bursts can be adjusted without reference to any steady burstfrequency. For example, a single stimulation burst of a predeterminedburst duration or a pattern of bursts of predetermined pulse width(s)and burst timing can be provided in response to a sensed signal.Furthermore, the duty cycle can be adjusted by adjusting the number ofbursts and/or adjusting the duration of one or more bursts, withoutrequiring the bursts to be delivered with a steady burst frequency.Examples of wave morphology include a square wave, triangle wave,sinusoidal wave, and waves with desired harmonic components to mimicwhite noise such as is indicative of naturally-occurring baroreflexstimulation. Additionally, various controller embodiments are capable ofcontrolling a duration of the stimulation. The sensor circuitry is usedto detect HF-related parameters to create an HF status index. Thecontroller compares the index to a target range stored in memory, andcontrols the neural stimulation based on the comparison in an attempt tokeep the response within the target range. The target range can beprogrammable and/or derived from past measurements.

FIG. 11 illustrates an implantable medical device (IMD) 1165 having aneural stimulation (NS) component 1166 and cardiac rhythm management(CRM) component 1167, according to various embodiments of the presentsubject matter. The illustrated device includes a controller 1168 andmemory 1169. According to various embodiments, the controller includeshardware, software, or a combination of hardware and software to performthe neural stimulation and CRM functions. For example, the programmedtherapy applications discussed in this disclosure are capable of beingstored as computer-readable instructions embodied in memory and executedby a processor. According to various embodiments, the controllerincludes a processor to execute instructions embedded in memory toperform the neural stimulation and CRM functions. The neural stimulationtherapy includes a heart failure therapy. Various embodiments includeanti-hypertension (AHT) therapy and anti-remodeling therapy (ART).Examples of CRM functions include bradycardia pacing, anti-tachycardiatherapies such as ATP, defibrillation and cardioversion, and CRT. Thecontroller also executes instructions to detect a tachyarrhythmia. Theillustrated device further includes a transceiver 1170 and associatedcircuitry for use to communicate with a programmer or another externalor internal device. Various embodiments include a telemetry coil.

The CRM therapy section 1167 includes components, under the control ofthe controller, to stimulate a heart and/or sense cardiac signals usingone or more electrodes. The illustrated CRM therapy section includes apulse generator 1171 for use to provide an electrical signal through anelectrode to stimulate a heart, and further includes sense circuitry1172 to detect and process sensed cardiac signals. An interface 1173 isgenerally illustrated for use to communicate between the controller 1168and the pulse generator 1171 and sense circuitry 1172. Three electrodesare illustrated as an example for use to provide CRM therapy. However,the present subject matter is not limited to a particular number ofelectrode sites. Each electrode may include its own pulse generator andsense circuitry. However, the present subject matter is not so limited.The pulse generating and sensing functions can be multiplexed tofunction with multiple electrodes.

The NS therapy section 1166 includes components, under the control ofthe controller, to stimulate a neural stimulation target and/or senseparameters associated with nerve activity or surrogates of nerveactivity such as blood pressure and respiration. Three interfaces 1174are illustrated for use to provide neural stimulation. However, thepresent subject matter is not limited to a particular number interfaces,or to any particular stimulating or sensing functions. Pulse generators1175 are used to provide electrical pulses to transducer or transducersfor use to stimulate a neural stimulation target. According to variousembodiments, the pulse generator includes circuitry to set, and in someembodiments change, the amplitude of the stimulation pulse, thefrequency of the stimulation pulse, the burst frequency of the pulse,and the morphology of the pulse such as a square wave, triangle wave,sinusoidal wave, and waves with desired harmonic components to mimicwhite noise or other signals. Sense circuits 1176 are used to detect andprocess signals from a sensor, such as a sensor of nerve activity, bloodpressure, respiration, and the like. The interfaces 1174 are generallyillustrated for use to communicate between the controller 1168 and thepulse generator 1175 and sense circuitry 1176. Each interface, forexample, may be used to control a separate lead. Various embodiments ofthe NS therapy section only includes a pulse generator to stimulate aneural target.

FIG. 12 shows a system diagram of an embodiment of amicroprocessor-based implantable device, according to variousembodiments. The controller of the device is a microprocessor 1277 whichcommunicates with a memory 1278 via a bidirectional data bus. Thecontroller could be implemented by other types of logic circuitry (e.g.,discrete components or programmable logic arrays) using a state machinetype of design, but a microprocessor-based system is preferable. As usedherein, the term “circuitry” should be taken to refer to either discretelogic circuitry or to the programming of a microprocessor. Shown in thefigure are three examples of sensing and pacing channels designated “A”through “C” comprising bipolar leads with ring electrodes 1279A-C andtip electrodes 1280A-C, sensing amplifiers 1281A-C, pulse generators1282A-C, and channel interfaces 1283A-C. Each channel thus includes apacing channel made up of the pulse generator connected to the electrodeand a sensing channel made up of the sense amplifier connected to theelectrode. The channel interfaces 1283A-C communicate bidirectionallywith the microprocessor 1277, and each interface may includeanalog-to-digital converters for digitizing sensing signal inputs fromthe sensing amplifiers and registers that can be written to by themicroprocessor in order to output pacing pulses, change the pacing pulseamplitude, and adjust the gain and threshold values for the sensingamplifiers. The sensing circuitry of the pacemaker detects a chambersense, either an atrial sense or ventricular sense, when an electrogramsignal (i.e., a voltage sensed by an electrode representing cardiacelectrical activity) generated by a particular channel exceeds aspecified detection threshold. Pacing algorithms used in particularpacing modes employ such senses to trigger or inhibit pacing. Theintrinsic atrial and/or ventricular rates can be measured by measuringthe time intervals between atrial and ventricular senses, respectively,and used to detect atrial and ventricular tachyarrhythmias.

The electrodes of each bipolar lead are connected via conductors withinthe lead to a switching network 1284 controlled by the microprocessor.The switching network is used to switch the electrodes to the input of asense amplifier in order to detect intrinsic cardiac activity and to theoutput of a pulse generator in order to deliver a pacing pulse. Theswitching network also enables the device to sense or pace either in abipolar mode using both the ring and tip electrodes of a lead or in aunipolar mode using only one of the electrodes of the lead with thedevice housing (can) 1285 or an electrode on another lead serving as aground electrode. A shock pulse generator 1286 is also interfaced to thecontroller for delivering a defibrillation shock via a pair of shockelectrodes 1287 and 1288 to the atria or ventricles upon detection of ashockable tachyarrhythmia.

Neural stimulation channels, identified as channels D and E, areincorporated into the device for delivering parasympathetic stimulationand/or sympathetic inhibition, where one channel includes a bipolar leadwith a first electrode 1289D and a second electrode 1290D, a pulsegenerator 1291D, and a channel interface 1292D, and the other channelincludes a bipolar lead with a first electrode 1289E and a secondelectrode 1290E, a pulse generator 1291, and a channel interface 1292E.Other embodiments may use unipolar leads in which case the neuralstimulation pulses are referenced to the can or another electrode. Thepulse generator for each channel outputs a train of neural stimulationpulses which may be varied by the controller as to amplitude, frequency,duty-cycle, and the like. In this embodiment, each of the neuralstimulation channels uses a lead which can be intravascularly disposednear an appropriate neural target. Other types of leads and/orelectrodes may also be employed. A nerve cuff electrode may be used inplace of an intravascularly disposed electrode to provide neuralstimulation. In some embodiments, the leads of the neural stimulationelectrodes are replaced by wireless links.

The figure illustrates a telemetry interface 1293 connected to themicroprocessor, which can be used to communicate with an externaldevice. The illustrated microprocessor 1277 is capable of performingneural stimulation therapy routines and myocardial stimulation routines.Examples of NS therapy routines include a heart failure therapy, ananti-hypertension therapy (AHT), and anti-remodeling therapy (ART).Examples of myocardial therapy routines include bradycardia pacingtherapies, anti-tachycardia shock therapies such as cardioversion ordefibrillation therapies, anti-tachycardia pacing therapies (ATP), andcardiac resynchronization therapies (CRT).

System Embodiments

FIG. 13 illustrates a system including an implantable medical device(IMD) 1394 and an external system or device 1395, according to variousembodiments of the present subject matter. Various embodiments of theIMD include a combination of NS and CRM functions. The IMD may alsodeliver biological agents and pharmaceutical agents. The external systemand the IMD are capable of wirelessly communicating data andinstructions. In various embodiments, for example, the external systemand IMD use telemetry coils to wirelessly communicate data andinstructions. Thus, the programmer can be used to adjust the programmedtherapy provided by the IMD, and the IMD can report device data (such asbattery and lead resistance) and therapy data (such as sense andstimulation data) to the programmer using radio telemetry, for example.According to various embodiments, the IMD stimulates/inhibits a neuraltarget to provide HF therapy.

The external system allows a user such as a physician or other caregiveror a patient to control the operation of the IMD and obtain informationacquired by the IMD. In one embodiment, external system includes aprogrammer communicating with the IMD bi-directionally via a telemetrylink. In another embodiment, the external system is a patient managementsystem including an external device communicating with a remote devicethrough a telecommunication network. The external device is within thevicinity of the IMD and communicates with the IMD bi-directionally via atelemetry link. The remote device allows the user to monitor and treat apatient from a distant location. The patient monitoring system isfurther discussed below.

The telemetry link provides for data transmission from implantablemedical device to external system. This includes, for example,transmitting real-time physiological data acquired by IMD, extractingphysiological data acquired by and stored in IMD, extracting therapyhistory data stored in implantable medical device, and extracting dataindicating an operational status of the IMD (e.g., battery status andlead impedance). Telemetry link also provides for data transmission fromexternal system to IMD. This includes, for example, programming the IMDto acquire physiological data, programming IMD to perform at least oneself-diagnostic test (such as for a device operational status), andprogramming the IMD to deliver at least one therapy.

FIG. 14 illustrates a system including an external device 1495, animplantable neural stimulator (NS) device 1496 and an implantablecardiac rhythm management (CRM) device 1497, according to variousembodiments of the present subject matter. Various aspects involve amethod for communicating between an NS device and a CRM device or othercardiac stimulator. In various embodiments, this communication allowsone of the devices 1496 or 1497 to deliver more appropriate therapy(i.e. more appropriate NS therapy or CRM therapy) based on data receivedfrom the other device. Some embodiments provide on-demandcommunications. In various embodiments, this communication allows eachof the devices to deliver more appropriate therapy (i.e. moreappropriate NS therapy and CRM therapy) based on data received from theother device. The illustrated NS device and the CRM device are capableof wirelessly communicating with each other, and the external system iscapable of wirelessly communicating with at least one of the NS and theCRM devices. For example, various embodiments use telemetry coils towirelessly communicate data and instructions to each other. In otherembodiments, communication of data and/or energy is by ultrasonic means.Rather than providing wireless communication between the NS and CRMdevices, various embodiments provide a communication cable or wire, suchas an intravenously-fed lead, for use to communicate between the NSdevice and the CRM device. In some embodiments, the external systemfunctions as a communication bridge between the NS and CRM devices.

FIG. 15 illustrates an IMD 1501 placed subcutaneously or submuscularlyin a patient's chest with lead(s) 1502 positioned to provide a CRMtherapy to a heart, and with lead(s) 1503 positioned to stimulate and/orinhibit neural traffic in a vagus nerve, by way of example and not byway of limitation, according to various embodiments. According tovarious embodiments, neural stimulation lead(s) 1503 are subcutaneouslytunneled to a neural target, and can have a nerve cuff electrode tostimulate the neural target. Some lead embodiments are intravascularlyfed into a vessel proximate to the neural target, and use transducer(s)within the vessel to transvascularly stimulate the neural target. Forexample, some embodiments target the vagus nerve using electrode(s)positioned within the internal jugular vein.

FIG. 16 illustrates an IMD 1601 with lead(s) 1602 positioned to providea CRM therapy to a heart, and with satellite transducers 1603 positionedto stimulate/inhibit a neural target, according to various embodiments.The satellite transducers are connected to the IMD, which functions asthe planet for the satellites, via a wireless link. Stimulation andcommunication can be performed through the wireless link. Examples ofwireless links include RF links and ultrasound links. Although notillustrated, some embodiments perform myocardial stimulation usingwireless links. Examples of satellite transducers include subcutaneouselectrodes, nerve cuff electrodes and intravascular electrodes.

FIG. 17 is a block diagram illustrating an embodiment of an externalsystem 1704. The external system includes a programmer, in someembodiments. In the illustrated embodiment, the external system includesa patient management system. As illustrated, the external system 1704 isa patient management system including an external device 1705, atelecommunication network 1706, and a remote device 1707. Externaldevice 1705 is placed within the vicinity of an IMD and includesexternal telemetry system 1708 to communicate with the IMD. Remotedevice(s) 1707 is in one or more remote locations and communicates withexternal device 1705 through network 1706, thus allowing a physician orother caregiver to monitor and treat a patient from a distant locationand/or allowing access to various treatment resources from the one ormore remote locations. The illustrated remote device 1707 includes auser interface 1709.

One of ordinary skill in the art will understand that the modules andother circuitry shown and described herein can be implemented usingsoftware, hardware, and combinations of software and hardware. As such,the term module is intended to encompass software implementations,hardware implementations, and software and hardware implementations.

The methods illustrated in this disclosure are not intended to beexclusive of other methods within the scope of the present subjectmatter. Those of ordinary skill in the art will understand, upon readingand comprehending this disclosure, other methods within the scope of thepresent subject matter. The above-identified embodiments, and portionsof the illustrated embodiments, are not necessarily mutually exclusive.These embodiments, or portions thereof, can be combined. In variousembodiments, the methods provided above are implemented as a computerdata signal embodied in a carrier wave or propagated signal, thatrepresents a sequence of instructions which, when executed by aprocessor cause the processor to perform the respective method. Invarious embodiments, methods provided above are implemented as a set ofinstructions contained on a computer-accessible medium capable ofdirecting a processor to perform the respective method. In variousembodiments, the medium is a magnetic medium, an electronic medium, oran optical medium.

Although specific embodiments have been illustrated and describedherein, it will be appreciated by those of ordinary skill in the artthat any arrangement which is calculated to achieve the same purpose maybe substituted for the specific embodiment shown. This application isintended to cover adaptations or variations of the present subjectmatter. It is to be understood that the above description is intended tobe illustrative, and not restrictive. Combinations of the aboveembodiments as well as combinations of portions of the above embodimentsin other embodiments will be apparent to those of skill in the art uponreviewing the above description. The scope of the present subject mattershould be determined with reference to the appended claims, along withthe full scope of equivalents to which such claims are entitled.

What is claimed is:
 1. A system, comprising: a stimulator configured todeliver a stimulation signal fir a heart failure therapy; and aprocessor and a non-transitory medium with instructions containedtherein for implementation by the processor, the processor configured tooperate on the instructions to: create heart failure status indicesusing heart failure parameters, the heart failure status indicesincluding a short term heart failure status index for detectinginadequate cardiac output and a long term heart failure status index fordetecting worsening or improving heart failure; and control thestimulator to deliver the heart failure therapy using both theshort-term heart failure status index and the long-term heart failureindex.
 2. The system of claim 1, wherein the processor is configured tooperate on the instructions to: obtain a first measurement of a heartfailure status and a second measurement of the heart failure status;create the heart failure indices using the first measurement and thesecond measurement; determine an adjustment for a heart failure therapyusing both the short-term heart failure index and the long-term heartfailure index; and control the stimulator to deliver the heart failuretherapy using the determined adjustment for the heart failure therapy.3. The system of claim 2, wherein in determining the adjustment for theheart failure therapy, the processor is configured to operate on theinstructions to determine an adjustment to a neural stimulation signal,the adjustment to the neural stimulation signal including an amplitudeof the neural stimulation signal, a frequency of the neural stimulationsignal, or a duration of the neural stimulation signal.
 4. The system ofclaim 2, wherein in obtaining at least one of the first measurement andthe second measurement, the processor is configured to operate on theinstructions to obtain, a heart rate variability (HRV) measurement,obtain a heart rate turbulence (HRT) measurement, obtain a respirationmeasurement, obtain an activity measurement, obtaining a heart soundmeasurement, or obtain a blood pressure measurement.
 5. The system ofclaim 2, wherein in determining the adjustment for the heart failuretherapy, the processor is configured to operate on the instructions totrend the heart failure index, and determine the adjustment for theheart failure therapy using the trend of the heart failure index.
 6. Thesystem of claim 1, wherein the stimulator includes a neural stimulatorconfigured to deliver a neural stimulation signal to stimulate anautonomic neural target for the heart failure therapy, the systemfurther comprising a myocardial stimulator configured to deliver amyocardial stimulation signal to stimulate myocardia, including deliverpaces to a heart to enforce a heart rate to meet metabolic demand,wherein the processor is configured to operate on the instructions tocontrol the neural stimulator and the myocardial stimulator to deliverthe heart failure therapy using the short-term heart failure statusindex and the long-term heart failure index, including control deliveryof the neural stimulation signal in response to a detecteddecompensation event to reduce a parasympathetic response.
 7. The systemof claim 1, further comprising a pacemaker, the processor configured tooperate on the instructions to enforce a heart rate using the pacemakerto meet metabolic demand.
 8. The system of claim 1, wherein the shortterm heart failure status index for detecting inadequate cardiac outputincludes: a short term status for detecting a decompensation event. 9.The system of claim 1, wherein the short term heart failure status indexfor detecting inadequate cardiac output includes a short term status fardetecting an approaching decompensation event, the processor configuredto operate on the instructions to cause the stimulator to apply neuralstimulation in response to detecting the approaching decompensationevent.
 10. The system of claim 1, wherein the processor is configured tooperate on the instructions to detect trends in the long term heartfailure status index.
 11. The system of claim 1, wherein the processoris configured to operate on the instructions to create heart failureindices using a composite index of two or more heart failure parameters.12. The system of claim 1, wherein the processor is configured tooperate on the instructions to reduce patient over stimulation using theheart failure status indices.
 13. The system of claim 1, wherein theprocessor is configured to operate on the instructions to manage batterypower accounting for both long-term heart failure status changes andshort-term heart failure status changes.
 14. The system of claim 1,wherein the processor is configured to operate on the instructions toavoid false positives accounting for both long-term heart failure statuschanges and short-term heart failure status changes, and toautomatically set a threshold to yield false alarms at a programmablefalse alarm rate, the programmable false alarm rate being programmableby a clinician.
 15. The system of claim 1, wherein the stimulatorincludes a neural stimulator configured to deliver a neural stimulationsignal to an autonomic neural target for the heart failure therapy. 16.The system of claim 15, wherein the processor is configured to operateon the instructions to control the stimulator to increase aparasympathetic response when the long-term index is less than a firstthreshold and decrease the parasympathetic response when the long-termindex exceeds a second threshold.
 17. The system of claim 1, wherein thestimulator includes a myocardial stimulator configured to deliver amyocardial stimulation signal for the heart failure therapy.
 18. Thesystem of claim 1, wherein the heart failure parameters includeexternally sensed weight or blood pressure.
 19. The system of claim 1,wherein the heart failure parameters include: data input by a physicianor by a patient; or pharmaceutical data; data from a population/clinicalstudy.
 20. The system of claim 1, wherein the processor is configured tooperate on the instructions to: provide an inference engine to createheart failure status indices from the heart failure parameters, or use aprobability function to create heart failure status indices from theheart failure parameters.